Project Name: UCLH Breast Cancer – Innovation and data strategy to improve the patient pathway and flow within the service.
Project Summary:
Female breast cancer is the most commonly diagnosed cancer, with an estimated 2.3 million new cases globally1.
In the United Kingdom, there are around 55,900 new breast cancer cases every year and it is the most common cancer, accounting for 15% of all new cancer cases2.
The increasing incidence of breast cancer and the most recent advances in breast oncology have led to significant expansion of the clinical practice. The implementation of new treatments requires more complex pathways and substantially higher clinic capacity with frequent review to monitor toxicity and ensure safe delivery.
The potential to derive benefit from routinely collected data is a major challenge for NHS. The NHS could learn from every patient interaction to continually improve services, better understand health and care needs, develop new treatments, support advances in data-driven technology and AI, and enable more efficient and patient-centered care3.
Over the last few years UCLH breast unit has faced unprecedented pressure particularly in outpatients, with patients receiving more treatments, with increased intensity and need for monitoring than ever before. This is demonstrated when viewing the rise in the increase in patient “follow-up” appointments which captures patients receiving treatment or on surveillance.
Overall, there has been an increase in the ratio of new to follow-up appointments from 1:10 to 1:17 which means that more outpatient appointments and treatment attendances must be accommodated within the existing clinic space and staffing resource. It is essential to capture this activity; there is much focus on the number of new patients diagnosed each year, but this only tells part of the story and suggests a much lower burden on the service. This increase in “on-treat burden” is set to continue and UCLH need to be able to analyse and interrogate data so that UCLH can identify new ways of efficient working and optimise patient care further.
The increasing clinical demand and the complexity of new treatment pathways highlights the need to optimise UCLH’s patients’ flow, review pathways and improve the quality of oncology care for breast cancer patients. In addition, creating ways to optimise the curation and linkage of clinical activity will enable better decision-making for direct care, commissioning, monitoring, evaluation and improvement of NHS services, policymaking, and research.
This project is designed to provide the link between the current clinical service to high-quality, timely data for service improvement, research, and innovation.
The CWP will achieve these aims through:
1) The recruitment and utilization of one full time equivalent (FTE) Clinical Fellow (ST3+) by UCLH for fifteen months.
2) The Clinical Fellow will be supported by the recruitment and utilization of a Business Intelligence Analyst (Band 8a) by UCLH for two days per week for fifteen months (0.4 FTE).
Planned Milestones:
1. Project Kick off and initiation of recruitment of ST3+ clinical research fellow and Band 8a Business intelligence analyst.
2. Completion of recruitment of Band 8a Business intelligence analyst and Shortlisting of candidates for ST3+ Clinical Fellow
3. Completion of recruitment of ST3+ Clinical Fellow
4. Initiation of EPIC and clinical database development and configuration.
5. Collection of baseline data, implementation of new Breast Cancer patient management protocols, completion of initial EPIC and clinical database configuration, initiation of clinical activity.
6. Data readout of 3 months clinical activity.
7. Data readout of 6 months clinical activity.
8. Data readout of 9 months clinical activity.
9. Data readout of 12 months Clinical activity.
10. Completion of ST3+ substantive role feasibility assessment and completion of project write up.
Expected Benefits:
Anticipated benefits for patients
This project will improve clinical data quality, thereby assisting the oncology department team:
- To enable patients to be screened earlier
- Increase patient access to the full treatment/ management pathway by improving identification of candidates for innovative therapies, genomic profiling or clinical trials (where appropriate)
- Enable more efficient patient progress through assessment and treatment; reducing time to progress through pathway- via securing an up-to-date patient pathway.
- To enhance pathway mapping and highlight opportunities to:
- Enhance patient experience via improvements to patient flow.
- Reduce and minimise of delays patients experience when transitioning from one treatment line to the next when there is disease progression.
- Improve patients’ outcomes- Through increased clinic capacity related to improved pathway efficiency and effectiveness.
Anticipated benefits for the CW Partner
- Development of data capture tool to accurately capture quantitative and qualitative patients’ clinical data.
- Optimisation of clinical documentation with the use of a shared tool will streamline clinical handover between different clinics lead by different lead UCLH clinicians.
- Improved segmentation of the UCLH patient population to support improved clarity on the eligibility for innovative therapies, genomic profiling and appropriate clinical research as defined by protocols.
- Increase in clinic capacity for service provision.
- Increase in Breast Cancer service efficiency in transitioning patients through treatment and management pathways.
- Improved data to support future analysis and research projects.
Anticipated Benefits for Novartis
- This project will support Novartis’ reputation and vision to make an impact in patients’ life by enhancing productivity and efficiency within the NHS.
- Ethical, professional, and transparent relationship between Novartis and the NHS.
- Better understanding of overall customers’ and patients’ needs
- Optimal use of NICE approved medicines (including Novartis medicines) in appropriate patients
Start Date & Duration: October 2023 for 23 months.
UK | October 2023 | 734690